class_docstr: defines how to transform encoder to decoder
  
  # Arguments
  bridge_type: currently only support "dense | densenonlinear"
  decoder_hiddenSize: hidden size of decoder
  bridge: keras layers used to do the transformation
  
  >>> bridge = Bridge.initialize("dense", 2)
  creating: createZooKerasBridge
  >>> dense = Dense(3)
  creating: createZooKerasDense
  >>> bridge = Bridge.initialize_from_keras_layer(dense)
  creating: createZooKerasBridge
docstr: bridge: keras layers used to do the transformation
docstr_tok: ["bridge",":","keras","layers","used","to","do","the","transformation"]
code: def initialize_from_keras_layer(cls, bridge):
      """
      bridge: keras layers used to do the transformation
      """
      return Bridge("customized", 0, bridge)
  
imports: from bigdl.nn.layer import Layer
  from zoo.pipeline.api.keras.layers import *
  from zoo.models.common import ZooModel
  from zoo.common.utils import callZooFunc
  from zoo.pipeline.api.keras.engine import ZooKerasLayer
  from zoo.pipeline.api.keras.models import Model
label_desc: Use image node_id 3 for calling the Bridge obj's underlying member method code with example usage: obj.initialize_from_keras_layer(cls, bridge) and returns: Bridge